Triple
T3980562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glaukopis |
E85745
|
entity |
| Predicate | epithetType |
P23283
|
FINISHED |
| Object | visual characteristic epithet |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: visual characteristic epithet | Statement: [Glaukopis, epithetType, visual characteristic epithet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: epithetType Context triple: [Glaukopis, epithetType, visual characteristic epithet]
-
A.
epithetOrTitle
chosen
Indicates that one entity serves as an epithet, honorific, or formal title used to designate or characterize another entity.
-
B.
eponymFor
Indicates that one entity gives its name to another entity, which is then named after it.
-
C.
honorificType
Indicates the type or category of honorific or formal title associated with an entity in a given context.
-
D.
honorificEponym
Indicates that one entity serves as an honorific namesake for another, typically recognizing or commemorating the person or entity in whose honor something is named.
-
E.
reasonForEpithet
Indicates the cause, motivation, or circumstance that explains why a particular epithet is applied to an entity.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69aed93908348190a26c8aaf4fab3e86 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa3ef7ac8190abe02f440ff83c43 |
completed | March 9, 2026, 4:50 p.m. |
| PD | Predicate disambiguation | batch_69aef8f492ac819089dbb9436dbcdd2b |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:33 p.m.